Journal
JOURNAL OF MEDICAL IMAGING AND RADIATION SCIENCES
Volume 51, Issue 4, Pages 671-677Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.jmir.2020.09.001
Keywords
Deep learning; Machine learning; Convolutional neural networks; Dose reduction; Generative adversarial networks
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Background and purpose: The use of AI in the process of CT image reconstruction may improve image quality of resultant images and therefore facilitate low-dose CT examinations. Methods: Articles in this review were gathered from multiple databases (Google Scholar, Ovid and Monash University Library Database). A total of 17 articles regarding AI use in CT image reconstruction was reviewed, including 1 white paper from GE Healthcare. Results: DLR algorithms performed better in terms of noise reduction abilities, and image quality preservation at low doses when compared to other reconstruction techniques. Conclusion: Further research is required to discuss clinical application and diagnostic accuracy of DLR algorithms, but AI is a promising dose-reduction technique with future computational advances.
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